# Source code for spacepy.irbempy.irbempy

    #!/usr/bin/env python
    # -*- coding: utf-8 -*-
    """
    module wrapper for irbem_lib
    Reference for this library
    https://sourceforge.net/projects/irbem/
    D. Boscher, S. Bourdarie, T. P. O'Brien, T. Guild, IRBEM library V4.3, 2004-2008

    Authors
    -------
    Josef Koller, Steve Morley

    Copyright 2010 Los Alamos National Security, LLC.
    """

    import itertools, numbers
    try:
        from collections.abc import Iterable
    except ImportError:
        from collections import Iterable
    import sys, os
    import warnings

    import numpy as np

    from spacepy import help, config
    import spacepy.coordinates as spc
    import spacepy.datamodel as dm
    try:
        from . import irbempylib as oplib
    except ImportError:
        if 'sphinx' in sys.argv[0]:
            warnings.warn('Could not import irbempylib. '
                          'You appear to be building docs, so ignoring this error.')
        else:
            raise
    import spacepy.toolbox as tb

    #check whether TS07_DATA_PATH is set, if not then set to spacepy's installed data directory
    if 'TS07_DATA_PATH' not in os.environ:
        import pkg_resources
        dataTS07D = os.path.join('data', 'TS07D')
        spdatapath = pkg_resources.resource_filename('spacepy', dataTS07D)
        os.environ['TS07_DATA_PATH'] = spdatapath #set environment variable here

    SYSAXES_TYPES = {'GDZ': {'sph': 0, 'car': None},
        'GEO': {'sph': None, 'car': 1}, 'GSM': {'sph': None, 'car': 2},
        'GSE': {'sph': None, 'car': 3}, 'SM': {'sph': None, 'car': 4},
        'GEI': {'sph': None, 'car': 5}, 'MAG': {'sph': None, 'car': 6},
        'SPH': {'sph': 7, 'car': None}, 'RLL': {'sph': 8, 'car': None},
        'TOD': {'sph': None, 'car': 12}, 'J2000': {'sph': None, 'car': 13}}

    # -----------------------------------------------
    def updateTS07Coeffs(path=None, force=False, verbose=False, **kwargs):
        '''Update coefficients for TS07 magnetic field model

        Parameters
        ----------
        path : str
            Base path for TS07 dynamic coefficients. If None (default)
            then the TS07_DATA_PATH environment variable is used.
        force : boolean
            If True (default is False) then missing paths will be created.
        verbose : boolean
            Print verbose output. Default is False.
        start : datetime.datetime or string
            Start time for archive retrieval. If start is a string then it should
            ISO8601 format (YYYY-MM-DDTHH:mm:SS). Defaults to 2007-01-01.
        end : datetime.datetime or string
            End time for archive retrieval. Required format same as start.
            Defaults to time of query (i.e. latest available).
        '''
        import glob, tarfile
        import spacepy.time as spt
        dt = spt.datetime
        if sys.version_info[0]<3:
            import urllib as u
        else:
            import urllib.request as u

        if 'user_agent' in config and config['user_agent']:
            class AppURLopener(u.FancyURLopener):
                version = config['user_agent']
            u._urlopener = AppURLopener()

        if not path:
            #test for TS07_DATA_PATH
            if 'TS07_DATA_PATH' in os.environ:
                path = os.environ['TS07_DATA_PATH']
            else:
                err_str = 'updateTS07Coeffs: Directory for TS07 data must be specified by \n' + \
                      'TS07_DATA_PATH environment variable or path keyword.'
                raise ValueError(err_str)

        #test that path exists, unless force keyword is set
        if not os.path.isdir(path):
            if force:
                os.makedirs(path, mode=0o777)
            else:
                raise IOError('updateTS07Coeffs: Specified path for TS07 is not valid - to force creation use "force" keyword')

        if 'start' not in kwargs:
            firstDate = dt.datetime(2007,1,1)
        else:
            firstDate = spt.Ticktock(kwargs['start']).UTC[0] #make sure it's a datetime
        if 'end' not in kwargs:
            lastDate = dt.datetime.now()
        else:
            lastDate = spt.Ticktock(kwargs['end']).UTC[0]

        baseURL = 'http://rbspgway.jhuapl.edu/models/magneticfieldmodeling/ts07d/coeffs_v02/'

        #make inventory of current TS07 data
        current_days = sorted(glob.glob(os.path.join(path,'Coeffs','*')))
        current_days = [os.path.split(dd)[-1] for dd in current_days if 'tgz' not in dd]
        current_dates = []
        for vals in current_days:
            try:
                adddate = spt.doy2date(int(vals.split('_')[0]),int(vals.split('_')[1]), dtobj=True)
            except ValueError: #not a valid date format
                continue
            current_dates.append(adddate)

        request_days = spt.tickrange(firstDate, lastDate, 1)
        timewant = set(request_days.UTC)
        timegot = set(current_dates)
        stillwant = sorted(list(timewant.difference(timegot)))

        print("Retrieving {2} requested files [{0} - {1}]".format(firstDate.date().isoformat(), lastDate.date().isoformat(), len(stillwant)))
        for day in stillwant:
            doy = spt.Ticktock(day).DOY[0]
            name = '{0}_{1:03d}'.format(day.year, doy)
            target = os.path.join(path, 'Coeffs', name)
            source = baseURL+'/{0}/'.format(day.year)+'{0}.tgz'.format(name)
            targetfile = os.path.join('{0}.tgz'.format(name))
            if verbose:
                print("\nFetching archive for {0}".format(day.date().isoformat()))
                tmp, report = u.urlretrieve(source, targetfile, reporthook=tb.progressbar)
            else:
                tmp, report = u.urlretrieve(source, targetfile)
            #if the file existed on the server then we won't get an HTML message back
            if 'html' not in report['content-type']:
                tar = tarfile.open(tmp, 'r:gz')
                tar.extractall(target)
                tar.close()
            #now remove tgz file
            os.unlink(tmp)

    # -----------------------------------------------
    def get_Bfield(ticks, loci, extMag='T01STORM', options=[1,0,0,0,0], omnivals=None):
        """
        call get_bfield in irbem lib and return a dictionary with the B-field vector and
        strenght.

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information
            - loci (Coords class) : containing spatial information
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained in Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table
            - (see Lstar documentation for further explanation)

        Returns
        =======
            - results (dictionary) : containing keys: Bvec, and Blocal

        Examples
        ========
        >>> import spacepy.time as spt
        >>> import spacepy.coordinates as spc
        >>> import spacepy.irbempy as ib
        >>> t = spt.Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> y = spc.Coords([[3,0,0],[2,0,0]], 'GEO', 'car')
        >>> ib.get_Bfield(t,y)
        {'Blocal': array([  976.42565251,  3396.25991675]),
           'Bvec': array([[ -5.01738885e-01,  -1.65104338e+02,   9.62365503e+02],
           [  3.33497974e+02,  -5.42111173e+02,   3.33608693e+03]])}

        See Also
        ========
        get_Lstar, find_Bmirror, find_magequator

        """

        # prepare input values for irbem call
        d = prep_irbem(ticks, loci, alpha=[], extMag=extMag, options=options, omnivals=omnivals)
        nTAI = len(ticks)
        badval = d['badval']
        kext = d['kext']
        sysaxes = d['sysaxes']
        iyearsat = d['iyearsat']
        idoysat = d['idoysat']
        secs = d['utsat']
        utsat = d['utsat']
        xin1 = d['xin1']
        xin2 = d['xin2']
        xin3 = d['xin3']
        magin = d['magin']

        results = dm.SpaceData()
        results['Blocal'] = np.zeros(nTAI)
        results['Bvec'] = np.zeros((nTAI,3))
        for i in np.arange(nTAI):
            BxyzGEO, Blocal = oplib.get_field1(kext,options,sysaxes,iyearsat[i],idoysat[i],secs[i], \
                xin1[i],xin2[i],xin3[i], magin[:,i])

            # take out all the odd 'bad values' and turn them into NaN
            if tb.feq(Blocal,badval): Blocal = np.NaN
            BxyzGEO[np.where( tb.feq(BxyzGEO, badval)) ] = np.NaN

            results['Blocal'][i] = Blocal
            results['Bvec'][i,:] = BxyzGEO

        return results

    # -----------------------------------------------
    def find_Bmirror(ticks, loci, alpha, extMag='T01STORM', options=[1,0,0,0,0], omnivals=None):
        """
        call find_mirror_point from irbem library and return a dictionary with values for
        Blocal, Bmirr and the GEO (cartesian) coordinates of the mirror point

        Parameters
        ==========
        ticks : Ticktock class
            containing time information
        loci : Coords class
            containing spatial information
        alpha : array-like
            containing the pitch angles
        extMag : str
            optional; will choose the external magnetic field model
            possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
            OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
            'T05', 'ALEX', 'TS07']
        options : array-like (optional)
            length=5 : explained in Lstar
        omnivals : dict (optional)
            if not provided, will use lookup table
            (see get_Lstar documentation for further explanation)

        Returns
        =======
        results : dictionary
            containing keys: Blocal, Bmirr, GEOcar

        Examples
        ========
        >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car')
        >>> ib.find_Bmirror(t,y,[90,80,60,10])
        {'Blocal': array([ 0.,  0.]),
         'Bmirr': array([ 0.,  0.]),
         'loci': Coords( [[ NaN  NaN  NaN]
         [ NaN  NaN  NaN]] ), dtype=GEO,car, units=['Re', 'Re', 'Re']}

        See Also
        ========
        get_Lstar, get_Bfield, find_magequator
        """

        # prepare input values for irbem call
        d = prep_irbem(ticks, loci, alpha, extMag=extMag, options=options, omnivals=omnivals)
        nTAI = len(ticks)
        badval = d['badval']
        kext = d['kext']
        sysaxes = d['sysaxes']
        iyearsat = d['iyearsat']
        idoysat = d['idoysat']
        secs = d['utsat']
        xin1 = d['xin1']
        xin2 = d['xin2']
        xin3 = d['xin3']
        magin = d['magin']
        #degalpha = d['degalpha']
        #nalp_max = d['nalp_max']
        #nalpha = d['nalpha']

        results = dm.SpaceData()
        results['Blocal'] = np.zeros(nTAI)
        results['Bmirr'] = np.zeros(nTAI)
        results['loci'] = ['']*nTAI
        for i in np.arange(nTAI):
            blocal, bmirr, GEOcoord = oplib.find_mirror_point1(kext,options,sysaxes, \
                iyearsat[i],idoysat[i],secs[i], xin1[i],xin2[i],xin3[i], alpha, magin[:,i])

            # take out all the odd 'bad values' and turn them into NaN
            if tb.feq(blocal,badval): blocal = np.NaN
            if tb.feq(bmirr,badval) : bmirr  = np.NaN
            GEOcoord[np.where( tb.feq(GEOcoord,badval)) ] = np.NaN

            results['Blocal'][i] = blocal
            results['Bmirr'][i] = bmirr
            results['loci'][i] = GEOcoord

        results['loci'] = spc.Coords(results['loci'], 'GEO', 'car')

        return results

    # -----------------------------------------------
    def find_magequator(ticks, loci, extMag='T01STORM', options=[1,0,0,0,0], omnivals=None):
        """
        call find_magequator from irbem library and return a dictionary with values for
        Bmin and the GEO (cartesian) coordinates of the magnetic equator

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information
            - loci (Coords class) : containing spatial information
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained in Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table
            - (see Lstar documentation for further explanation)

        Returns
        =======
            - results (dictionary) : containing keys: Bmin, Coords instance with GEO coordinates of
                the magnetic equator

        Examples
        ========
        >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car')
        >>> op.find_magequator(t,y)
        {'Bmin': array([  945.63652413,  3373.64496167]),
            'loci': Coords( [[ 2.99938371  0.00534151 -0.03213603]
            [ 2.00298822 -0.0073077   0.04584859]] ), dtype=GEO,car, units=['Re', 'Re', 'Re']}

        See Also
        ========
        get_Lstar, get_Bfield, find_Bmirr
        """
        # prepare input values for irbem call
        d = prep_irbem(ticks, loci, alpha=[], extMag=extMag, options=options, omnivals=omnivals)
        nTAI = len(ticks)
        badval = d['badval']
        kext = d['kext']
        sysaxes = d['sysaxes']
        iyearsat = d['iyearsat']
        idoysat = d['idoysat']
        secs = d['utsat']
        xin1 = d['xin1']
        xin2 = d['xin2']
        xin3 = d['xin3']
        magin = d['magin']

        results = {}
        results['Bmin'] = np.zeros(nTAI)
        results['loci'] = ['']*nTAI
        for i in np.arange(nTAI):
            bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                iyearsat[i],idoysat[i],secs[i], xin1[i],xin2[i],xin3[i],magin[:,i])

            # take out all the odd 'bad values' and turn them into NaN
            if tb.feq(bmin,badval): bmin = np.NaN
            GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN

            results['Bmin'][i] = bmin
            results['loci'][i] = GEOcoord

        results['loci'] = spc.Coords(results['loci'], 'GEO', 'car')

        return results

    # -----------------------------------------------
    def find_LCDS(ticks, alpha, extMag='T01STORM', options=[1,0,0,0,0], omnivals=None, tol=0.05, bracket=[3,12], mlt=0, **kwargs):
        """
        Find the last closed drift shell (LCDS) for a given equatorial pitch angle.

        Uses the IRBEM library to determine L* and searches via bisection to find LCDS
        to a given tolerance in R (radial distance along GSM equator at local midnight).

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information **for a single time**
            - alpha (numeric) : equatorial pitch angle for search
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained in Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table
            - (see Lstar documentation for further explanation)
            - tol (float) : tolerance for search in radial distance
            - bracket (list): X-GSM coordinates to bracket bisection search

        Returns
        =======
            results (SpaceData, dictionary-like): contains keys LCDS, K, AlphaEq and UTC

        Examples
        ========
        >>> t = spacepy.time.Ticktock(['2002-02-02T12:00:00'], 'ISO')
        >>> spacepy.irbempy.find_LCDS(t, 90, extMag='T89')

        See Also
        ========
        get_Lstar, get_Bfield, find_Bmirr
        """
        # prepare input values for irbem call
        nTAI = len(ticks)

        #First set inner bracket (default to R of 3)
        try:
            assert len(bracket)==2
        except:
            raise ValueError('Specified initial bracket is invalid')

        if not isinstance(alpha, Iterable): alpha = [alpha]
        results = dm.SpaceData()
        if len(alpha)!=1:
            results['LCDS'] = dm.dmfilled([nTAI,len(alpha)])
            results['K'] = dm.dmfilled([nTAI,len(alpha)])
        else:
            results['LCDS'] = dm.dmfilled([nTAI,])
            results['K'] = dm.dmfilled([nTAI,])
        results['LCDS'].attrs['DESCRIPTION'] = "Last closed drift shell calculated with SpacePy's irbempy module"
        results['LCDS'].attrs['UNITS'] = "dimensionless"
        results['LCDS'].attrs['DEPEND_0'] = "UTC"
        results['LCDS'].attrs['DEPEND_1'] = "K"
        results['LCDS'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag)
        results['K'].attrs['DESCRIPTION'] = "Modified 2nd adiabatic invariant at LCDS"
        results['K'].attrs['UNITS'] = "R_E.G^{1/2}"
        results['K'].attrs['DEPEND_0'] = "UTC"
        results['K'].attrs['DEPEND_1'] = "AlphaEq"
        results['K'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag)
        results['UTC'] = ticks.UTC
        results['AlphaEq'] = dm.dmarray(alpha,
                                        attrs={'DESCRIPTION': 'Equatorial pitch angle for LCDS calculation',
                                               'UNITS': 'degrees'})

        mlt *= 15 #hours to degrees
        mlt = np.deg2rad(mlt)

        for idxt, tt in enumerate(ticks):
            if not omnivals:
                #prep_irbem will get omni if not specified, but to save on repeated calls, do it once here
                import spacepy.omni as omni
                omnivals = omni.get_omni(tt)
            for idxa, pa in enumerate(alpha):
                b1x = -1.0*bracket[0]*np.cos(mlt)
                b1y = -1.0*bracket[0]*np.sin(mlt)
                loci_brac1 = spc.Coords([b1x,b1y,0], 'GSM', 'car')
                if 'verbose' in kwargs: print('Initial inner bracket: {0}'.format(loci_brac1))

                d = prep_irbem(tt, loci_brac1, alpha=[pa], extMag=extMag, options=options, omnivals=omnivals)
                badval = d['badval']
                kext = d['kext']
                sysaxes = d['sysaxes']
                iyearsat = d['iyearsat']
                idoysat = d['idoysat']
                secs = d['utsat']
                xin1 = d['xin1']
                xin2 = d['xin2']
                xin3 = d['xin3']
                magin = d['magin']
                nTtoG = 1.0e-5

                bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                    iyearsat[0],idoysat[0],secs[0], xin1[0],xin2[0],xin3[0],magin[:,0])

                # take out all the odd 'bad values' and turn them into NaN
                if tb.feq(bmin,badval): bmin = np.NaN
                GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN
                #Now get Lstar at this location...
                if GEOcoord[0]!=np.NaN:
                    pos1 = spc.Coords(GEOcoord, 'GEO', 'car')
                    LS1 = get_Lstar(tt, pos1, pa, extMag=extMag, options=options, omnivals=omnivals)
                    if np.isnan(LS1['Lstar']).any():
                        raise ValueError('Specified inner bracket ({0}) is on an open drift shell'.format(loci_brac1))
                    LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG)
                else:
                    raise ValueError('Specified inner bracket ({0}) is on an open drift shell'.format(loci_brac1))
                #print('L* at inner bracket: {0}'.format(LS1['Lstar']))
                LCDS, LCDS_K = LS1['Lstar'][0], LS1['K'][0]

                #Set outer bracket (default to R of 12)
                b2x = -1.0*bracket[1]*np.cos(mlt)
                b2y = -1.0*bracket[1]*np.sin(mlt)
                loci_brac2 = spc.Coords([b2x,b2y,0], 'GSM', 'car')
                if 'verbose' in kwargs: print('Initial outer bracket: {0}'.format(loci_brac2))

                d2 = prep_irbem(tt, loci_brac2, alpha=[pa], extMag=extMag, options=options, omnivals=omnivals)
                badval = d2['badval']
                kext = d2['kext']
                sysaxes = d2['sysaxes']
                iyearsat = d2['iyearsat']
                idoysat = d2['idoysat']
                secs = d2['utsat']
                xin1 = d2['xin1']
                xin2 = d2['xin2']
                xin3 = d2['xin3']
                magin = d2['magin']

                bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                    iyearsat[0],idoysat[0],secs[0], xin1[0],xin2[0],xin3[0],magin[:,0])

                # take out all the odd 'bad values' and turn them into NaN
                if tb.feq(bmin,badval): bmin = np.NaN
                GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN
                #Now get Lstar at this location...
                if GEOcoord[0]!=np.NaN:
                    pos2 = spc.Coords(GEOcoord, 'GEO', 'car')
                    LS2 = get_Lstar(tt, pos2, pa, extMag=extMag, options=options, omnivals=omnivals)
                    if not np.isnan(LS2['Lstar']).any():
                        raise ValueError('Specified outer bracket is on a closed drift shell')
                else:
                    LS2 = {'Lstar': np.NaN}
                #print('L* at outer bracket: {0}; Xgsm = {1}'.format(LS2['Lstar'], loci_brac2.x))

                #now search by bisection
                while (tb.hypot(loci_brac2.x, loci_brac2.y) - tb.hypot(loci_brac1.x, loci_brac1.y) > tol):
                    newdist = (tb.hypot(loci_brac2.x, loci_brac2.y) + tb.hypot(loci_brac1.x, loci_brac1.y))/2.0
                    newx = -1.0*newdist*np.cos(mlt)
                    newy = -1.0*newdist*np.sin(mlt)
                    pos_test = spc.Coords([newx, newy, 0], 'GSM', 'car')

                    dtest = prep_irbem(tt, pos_test, alpha=[pa], extMag=extMag, options=options, omnivals=omnivals)
                    badval = dtest['badval']
                    kext = dtest['kext']
                    sysaxes = dtest['sysaxes']
                    iyearsat = dtest['iyearsat']
                    idoysat = dtest['idoysat']
                    secs = dtest['utsat']
                    xin1 = dtest['xin1']
                    xin2 = dtest['xin2']
                    xin3 = dtest['xin3']
                    magin = dtest['magin']

                    bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                        iyearsat[0],idoysat[0],secs[0], xin1[0],xin2[0],xin3[0],magin[:,0])
                    # take out all the odd 'bad values' and turn them into NaN
                    if tb.feq(bmin,badval): bmin = np.NaN
                    GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN
                    #print('bmin, GEOcoord = {0},{1}'.format(bmin, GEOcoord))
                    if not (np.isnan(bmin)):
                        #Now get Lstar at this location...
                        postry = spc.Coords(GEOcoord, 'GEO', 'car')
                        LStry = get_Lstar(tt, postry, pa, extMag=extMag, options=options, omnivals=omnivals)
                        LStry['K'] = LStry['Xj']*np.sqrt(LStry['Bmirr']*nTtoG)
                    else:
                        LStry = {'Lstar': np.NaN, 'K': np.NaN}
                    if 'verbose' in kwargs: print('L* at test point: {0}; Xgsm = {1}'.format(LStry['Lstar'], pos_test))

                    if np.isnan(LStry['Lstar']).any():
                        loci_brac2 = pos_test
                    else:
                        loci_brac1 = pos_test
                        LCDS, LCDS_K = LStry['Lstar'][0], LStry['K'][0]
                try:
                    results['LCDS'][idxt, idxa] = LCDS
                    results['K'][idxt, idxa] = LCDS_K
                except IndexError:
                    results['LCDS'][idxt] = LCDS
                    results['K'][idxt] = LCDS_K

        results['LCDS'] = results['LCDS']
        results['K'] = results['K']

        return results

    # -----------------------------------------------
    def find_LCDS_K(ticks, K, extMag='T01STORM', options=[1,1,3,0,0], omnivals=None, tol=0.05, bracket=[3,12], mlt=0, **kwargs):
        """
        Find the last closed drift shell (LCDS) for a given equatorial pitch angle.

        Uses the IRBEM library to determine L* and searches via bisection to find LCDS
        to a given tolerance in R (radial distance along GSM equator at local midnight).

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information **for a single time**
            - alpha (numeric) : equatorial pitch angle for search
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained in Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table
            - (see Lstar documentation for further explanation)
            - tol (float) : tolerance for search in radial distance
            - bracket (list): X-GSM coordinates to bracket bisection search

        Returns
        =======
            results (SpaceData, dictionary-like): contains keys LCDS, K, AlphaEq and UTC

        Examples
        ========
        >>> t = spacepy.time.Ticktock(['2002-02-02T12:00:00'], 'ISO')
        >>> spacepy.irbempy.find_LCDS(t, 90, extMag='T89')

        See Also
        ========
        get_Lstar, get_Bfield, find_Bmirr
        """
        # prepare input values for irbem call
        nTAI = len(ticks)
        Aopt = [0]
        Aopt.extend(options[1:])

        #First set inner bracket (default to R of 3)
        try:
            assert len(bracket)==2
        except:
            raise ValueError('Specified initial bracket is invalid')

        if not isinstance(K, Iterable): K = [K]
        results = dm.SpaceData()
        if len(K)!=1:
            results['LCDS'] = dm.dmfilled([nTAI,len(K)])
            results['AlphaEq'] = dm.dmfilled([nTAI,len(K)])
            results['Success'] = dm.dmfilled([nTAI,len(K)], fillval='Success', dtype='|S24')
        else:
            results['LCDS'] = dm.dmfilled([nTAI,])
            results['AlphaEq'] = dm.dmfilled([nTAI,])
        results['LCDS'].attrs['DESCRIPTION'] = "Last closed drift shell calculated with SpacePy's irbempy module"
        results['LCDS'].attrs['UNITS'] = "dimensionless"
        results['LCDS'].attrs['DEPEND_0'] = "UTC"
        results['LCDS'].attrs['DEPEND_1'] = "K"
        results['LCDS'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag)
        results['AlphaEq'].attrs['DESCRIPTION'] = "Modified 2nd adiabatic invariant at LCDS"
        results['AlphaEq'].attrs['UNITS'] = "R_E.G^{1/2}"
        results['AlphaEq'].attrs['MODEL'] = "{0} (IRBEM implementation)".format(extMag)
        results['UTC'] = ticks.UTC
        results['K'] = dm.dmarray(K, attrs={'DESCRIPTION': 'Equatorial pitch angle for LCDS calculation',
                                               'UNITS': 'degrees'})

        mlt *= 15 #hours to degrees
        mlt = np.deg2rad(mlt)

        for idxt, tt in enumerate(ticks):
            if not omnivals:
                #prep_irbem will get omni if not specified, but to save on repeated calls, do it once here
                import spacepy.omni as omni
                omnivals = omni.get_omni(tt)
            for idxk, k_i in enumerate(K):
                b1x = -1.0*bracket[0]*np.cos(mlt)
                b1y = -1.0*bracket[0]*np.sin(mlt)
                loci_brac1 = spc.Coords([b1x,b1y,0], 'GSM', 'car')
                if 'verbose' in kwargs: print('Initial inner bracket: {0}'.format(loci_brac1))

                d = prep_irbem(tt, loci_brac1, extMag=extMag, options=options, omnivals=omnivals)
                badval = d['badval']
                kext = d['kext']
                sysaxes = d['sysaxes']
                iyearsat = d['iyearsat']
                idoysat = d['idoysat']
                secs = d['utsat']
                xin1 = d['xin1']
                xin2 = d['xin2']
                xin3 = d['xin3']
                magin = d['magin']
                nTtoG = 1.0e-5
                pa = np.NaN

                bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                    iyearsat[0],idoysat[0],secs[0], xin1[0],xin2[0],xin3[0],magin[:,0])

                # take out all the odd 'bad values' and turn them into NaN
                if tb.feq(bmin,badval): bmin = np.NaN
                GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN
                #Now get Lstar at this location...
                if np.isfinite(GEOcoord[0]):
                    pos1 = spc.Coords(GEOcoord, 'GEO', 'car')
                    pa = AlphaOfK(tt, pos1, k_i, extMag=extMag, options=Aopt, omnivals=omnivals)
                    LS1 = get_Lstar(tt, pos1, pa, extMag=extMag, options=options, omnivals=omnivals)
                    if np.isnan(LS1['Lstar']).any():
                        try:
                            results['LCDS'][idxt, idxk] = np.NaN
                            results['AlphaEq'][idxt, idxk] = pa
                            results['Success'][idxt, idxk] = 'Invalid inner bracket'
                        except IndexError:
                            results['LCDS'][idxt] = np.NaN
                            results['AlphaEq'][idxt] = pa
                            results['Success'][idxt] = 'Invalid inner bracket'
                        continue
                    LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG)
                else:
                    try:
                        results['LCDS'][idxt, idxk] = np.NaN
                        results['AlphaEq'][idxt, idxk] = pa
                        results['Success'][idxt, idxk] = 'Invalid inner bracket'
                    except IndexError:
                        results['LCDS'][idxt] = np.NaN
                        results['AlphaEq'][idxt] = pa
                        results['Success'][idxt] = 'Invalid inner bracket'
                    continue

                #print('L* at inner bracket: {0}'.format(LS1['Lstar']))
                LCDS, LCDS_PA = LS1['Lstar'][0], pa

                #Set outer bracket (default to R of 12)
                b2x = -1.0*bracket[1]*np.cos(mlt)
                b2y = -1.0*bracket[1]*np.sin(mlt)
                loci_brac2 = spc.Coords([b2x,b2y,0], 'GSM', 'car')
                if 'verbose' in kwargs: print('Initial outer bracket: {0}'.format(loci_brac2))

                d2 = prep_irbem(tt, loci_brac2, extMag=extMag, options=options, omnivals=omnivals)
                badval = d2['badval']
                kext = d2['kext']
                sysaxes = d2['sysaxes']
                iyearsat = d2['iyearsat']
                idoysat = d2['idoysat']
                secs = d2['utsat']
                xin1 = d2['xin1']
                xin2 = d2['xin2']
                xin3 = d2['xin3']
                magin = d2['magin']

                bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                    iyearsat[0],idoysat[0],secs[0], xin1[0],xin2[0],xin3[0],magin[:,0])

                # take out all the odd 'bad values' and turn them into NaN
                if tb.feq(bmin,badval): bmin = np.NaN
                GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN
                #Now get Lstar at this location...
                if np.isfinite(GEOcoord[0]):
                    pos2 = spc.Coords(GEOcoord, 'GEO', 'car')
                    pa = AlphaOfK(tt, pos2, k_i, extMag=extMag, options=Aopt, omnivals=omnivals)
                    LS2 = get_Lstar(tt, pos2, pa, extMag=extMag, options=options, omnivals=omnivals)
                    if not np.isnan(LS2['Lstar']).any():
                        try:
                            results['LCDS'][idxt, idxk] = np.NaN
                            results['AlphaEq'][idxt, idxk] = pa
                            results['Success'][idxt, idxk] = 'Invalid outer bracket'
                        except IndexError:
                            results['LCDS'][idxt] = np.NaN
                            results['AlphaEq'][idxt] = pa
                            results['Success'][idxt] = 'Invalid outer bracket'
                        continue
                else:
                    LS2 = {'Lstar': np.NaN}
                #print('L* at outer bracket: {0}; Xgsm = {1}'.format(LS2['Lstar'], loci_brac2.x))

                #now search by bisection
                while (tb.hypot(loci_brac2.x, loci_brac2.y) - tb.hypot(loci_brac1.x, loci_brac1.y) > tol):
                    newdist = (tb.hypot(loci_brac2.x, loci_brac2.y) + tb.hypot(loci_brac1.x, loci_brac1.y))/2.0
                    newx = -1.0*newdist*np.cos(mlt)
                    newy = -1.0*newdist*np.sin(mlt)
                    pos_test = spc.Coords([newx, newy, 0], 'GSM', 'car')

                    dtest = prep_irbem(tt, pos_test, extMag=extMag, options=options, omnivals=omnivals)
                    badval = dtest['badval']
                    kext = dtest['kext']
                    sysaxes = dtest['sysaxes']
                    iyearsat = dtest['iyearsat']
                    idoysat = dtest['idoysat']
                    secs = dtest['utsat']
                    xin1 = dtest['xin1']
                    xin2 = dtest['xin2']
                    xin3 = dtest['xin3']
                    magin = dtest['magin']

                    bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                        iyearsat[0],idoysat[0],secs[0], xin1[0],xin2[0],xin3[0],magin[:,0])
                    # take out all the odd 'bad values' and turn them into NaN
                    if tb.feq(bmin,badval): bmin = np.NaN
                    GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN
                    #print('bmin, GEOcoord = {0},{1}'.format(bmin, GEOcoord))
                    if not (np.isnan(bmin)):
                        #Now get Lstar at this location...
                        postry = spc.Coords(GEOcoord, 'GEO', 'car')
                        pa = AlphaOfK(tt, postry, k_i, extMag=extMag, options=Aopt, omnivals=omnivals)
                        LStry = get_Lstar(tt, postry, pa, extMag=extMag, options=options, omnivals=omnivals)
                        LStry['K'] = LStry['Xj']*np.sqrt(LStry['Bmirr']*nTtoG)
                    else:
                        LStry = {'Lstar': np.NaN, 'K': np.NaN}
                    if 'verbose' in kwargs: print('L* at test point: {0}; Xgsm = {1}'.format(LStry['Lstar'], pos_test))

                    if np.isnan(LStry['Lstar']).any():
                        loci_brac2 = pos_test
                    else:
                        loci_brac1 = pos_test
                        LCDS, LCDS_PA = LStry['Lstar'][0], pa
                try:
                    results['LCDS'][idxt, idxk] = LCDS
                    results['AlphaEq'][idxt, idxk] = LCDS_PA
                except IndexError:
                    results['LCDS'][idxt] = LCDS
                    results['AlphaEq'][idxt] = LCDS_PA

        results['LCDS'] = results['LCDS']
        results['AlphaEq'] = results['AlphaEq']

        return results

    # -----------------------------------------------
    def AlphaOfK(ticks, loci, K, extMag='T01STORM', options=[0,0,3,0,0], omnivals=None):
        """
        Find the equatorial pitch angle corresponding to a given second invariant K.

        Uses the IRBEM library to determine K and searches via bisection to find Alpha(K).

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information **for a single time**
            - loci (Coords class) : containing position information **for a single point**
            - K (numeric) : value of second invariant (K) for search
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained in Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table
            - (see Lstar documentation for further explanation)
            - tol (float) : tolerance for search in radial distance
            - bracket (list): X-GSM coordinates to bracket bisection search

        Returns
        =======
            AlphaEq : equatorial pitch angle corresponding to K

        Examples
        ========
        >>> t = spacepy.time.Ticktock(['2002-09-01T04:00:00'], 'ISO')
        >>> loci = spacepy.coordinates.Coords([-4,0,0], 'GSM', 'car')
        >>> spacepy.irbempy.AlphaOfK(t, loci, 0.11, extMag='T89')
        48.984375

        See Also
        ========
        get_Lstar, get_Bfield, find_Bmirr, find_LCDS
        """
        # prepare input values for irbem call
        d = prep_irbem(ticks, loci, extMag=extMag, options=options, omnivals=omnivals)
        nTAI = len(ticks)
        badval = d['badval']
        kext = d['kext']
        sysaxes = d['sysaxes']
        iyearsat = d['iyearsat']
        idoysat = d['idoysat']
        secs = d['utsat']
        xin1 = d['xin1']
        xin2 = d['xin2']
        xin3 = d['xin3']
        magin = d['magin']
        nTtoG = 1.0e-5

        outvals = np.zeros(nTAI)
        outvals.fill(np.NaN)
        for i in np.arange(nTAI):
            bmin, GEOcoord = oplib.find_magequator1(kext,options,sysaxes,\
                             iyearsat[i],idoysat[i],secs[i], xin1[i],xin2[i],xin3[i],magin[:,i])

            # take out all the odd 'bad values' and turn them into NaN
            if tb.feq(bmin,badval): bmin = np.NaN
            GEOcoord[np.where( tb.feq(GEOcoord, badval)) ] = np.NaN

            pa0 = 90 #start with equatorially mirroring
            #Now get K for initial alpha at this location...
            if np.isfinite(GEOcoord[0]):
                pos1 = spc.Coords(GEOcoord, 'GEO', 'car')
                LS1 = get_Lstar(ticks[i], pos1, pa0, extMag=extMag, options=options, omnivals=omnivals)
                if np.isnan(LS1['Xj']).any():
                    return np.NaN
                LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG)
            else:
                #print('i = {0}, skipping because of bad position'.format(i))
                continue
            K0 = LS1['K'][0]

            if np.abs(K0-K) < 1e-3:
                outvals[i] = pa0
                #print('i= {0}, found alpha = {1}'.format(i, pa0))
                continue

            Done, count = False, 0
            pa_upper, pa_lower, pa_test = pa0, 0, 30
            while not Done:
                #print('Testing PA={0}'.format(pa_test))
                #Now get K for initial alpha at this location...
                LS1 = get_Lstar(ticks[i], pos1, pa_test, extMag=extMag, options=options, omnivals=omnivals)
                if np.isnan(LS1['Xj']).any():
                    break
                LS1['K'] = LS1['Xj']*np.sqrt(LS1['Bmirr']*nTtoG)
                #print('L* at inner bracket: {0}'.format(LS1['Lstar']))
                K_test = LS1['K'][0]

                if np.abs(K_test-K) < 1e-3:
                    #print('***Found K={0} (Req. {1}) at Alpha={2}'.format(K_test, K, pa_test))
                    outvals[i] = pa_test
                    break
                #print('Not Done: Kfound = {0}, Kwant = {1}'.format(K_test, K))
                if K_test > K: # K is too large, hence alpha is too small, increase.
                    pa_lower = pa_test
                    #print('Reset lower bound. U,L = {0},{1}'.format(pa_upper, pa_lower))
                else: # K is too small, hence alpha is too large, reduce
                    pa_upper = pa_test
                    #print('Reset upper bound. U,L = {0},{1}'.format(pa_upper, pa_lower))
                pa_test = pa_lower+np.abs((pa_upper-pa_lower))/2.0
                #print('Change alpha to {0}'.format(pa_test))
                count += 1
                if count>20: break
        return outvals

    # -----------------------------------------------
    def find_footpoint(ticks, loci, extMag='T01STORM', options=[1,0,3,0,0], hemi='same', alt=100, omnivals=None):
        """
        call find_foot_point1 from irbem library and return a dictionary with values for
        Bmin and the GEO (cartesian) coordinates of the magnetic equator

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information
            - loci (Coords class) : containing spatial information
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained in Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table
            - (see Lstar documentation for further explanation)
            - hemi (string) : optional (valid cases are 'same', 'other', 'north' or 'south')
                              will set the target hemisphere for tracing the footpoint
            - alt (numeric) : optional keyword to set stop height [km] of fieldline trace (default 100km)

        Returns
        =======
            - results (spacepy.datamodel.SpaceData) : containing keys
                       Bfoot    - Magnitude of B-field at footpoint [nT]
                       loci     - Coords instance with GDZ coordinates of the magnetic footpoint [alt, lat, lon]
                       Bfootvec - Components of B-field at footpoint in cartesian GEO coordinates [nT]

        Examples
        ========
        >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> y = Coords([[3,0,0],[3,0,0]], 'GEO', 'car')
        >>> spacepy.irbempy.find_footpoint(t, y)
        {'Bfoot': array([ 47559.04643444,  47542.84688657]),
         'Bfootvec': array([[-38428.07217246,   4497.31549786, -27657.19291928],
               [-38419.08514332,   4501.45390964, -27641.14866517]]),
         'loci': Coords( [[ 99.31443778  55.71415787 -10.21888955]
         [ 99.99397026  55.70716296 -10.22797462]] ), dtype=GDZ,sph, units=['km', 'deg', 'deg']}

        See Also
        ========
        get_Lstar, get_Bfield, find_Bmirr, find_magequator
        """
        # prepare input values for irbem call
        d = prep_irbem(ticks, loci, extMag=extMag, options=options, omnivals=omnivals)
        nTAI = len(ticks)
        badval = d['badval']
        kext = d['kext']
        sysaxes = d['sysaxes']
        iyearsat = d['iyearsat']
        idoysat = d['idoysat']
        secs = d['utsat']
        xin1 = d['xin1']
        xin2 = d['xin2']
        xin3 = d['xin3']
        magin = d['magin']

        hemi_dict = {'same': 0, 'north': 1, 'south': -1, 'other': 2}
        if hemi.lower() in ['same', 'other', 'north', 'south']:
            hemi_flag = hemi_dict[hemi.lower()]
        else:
            raise ValueError('Option for hemisphere to trace to ({0}) is invalid.\n'.format(hemi) +
                             'Valid options are: same, other, north and south')

        results = dm.SpaceData()
        results['Bfoot'] = np.zeros(nTAI)
        results['Bfootvec'] = np.zeros([nTAI, 3])
        results['loci'] = ['']*nTAI
        for i in np.arange(nTAI):
            xfoot, bfoot, bfootmag = oplib.find_foot_point1(kext, options, sysaxes,\
                iyearsat[i], idoysat[i], secs[i], xin1[i], xin2[i], xin3[i], alt, hemi_flag, magin[:,i])

            # take out all the odd 'bad values' and turn them into NaN
            if tb.feq(bfootmag,badval): bmin = np.NaN
            xfoot[np.where( tb.feq(xfoot, badval)) ] = np.NaN
            bfoot[np.where( tb.feq(bfoot, badval)) ] = np.NaN

            results['Bfoot'][i] = bfootmag
            results['loci'][i] = xfoot
            results['Bfootvec'][i] = bfoot

        results['loci'] = spc.Coords(results['loci'], 'GDZ', 'sph')
        results.attrs
        return results

    # -----------------------------------------------
    def coord_trans(loci, returntype, returncarsph ):
        """
        thin layer to call coor_trans1 from irbem lib
        this will convert between systems GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL

        Parameters
        ==========
            - loci (Coords instance) : containing coordinate information, can contain n points
            - returntype (str) : describing system as GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL
            - returncarsph (str) : cartesian or spherical units 'car', 'sph'

        Returns
        =======
            - xout (ndarray) : values after transformation in (n,3) dimensions

        Examples
        ========
        >>> c = Coords([[3,0,0],[2,0,0]], 'GEO', 'car')
        >>> c.ticks = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> coord_trans(c, 'GSM', 'car')
        array([[ 2.8639301 , -0.01848784,  0.89306361],
        [ 1.9124434 ,  0.07209424,  0.58082929]])

        See Also
        ========
        sph2car, car2sph

        """
        sysaxesin = get_sysaxes( loci.dtype, loci.carsph )
        sysaxesout = get_sysaxes( returntype, returncarsph )

        # swap carsph if sysaxesout is None
        if (sysaxesout is None) and (returncarsph == 'sph'):
            sysaxesout = get_sysaxes( returntype, 'car' )
            aflag = True
        elif (sysaxesout is None) and (returncarsph == 'car'):
            sysaxesout = get_sysaxes( returntype, 'sph' )
            aflag = True
        else:
            aflag = False

        xout = np.zeros(np.shape(loci.data))
        for i in np.arange(len(loci)):
            iyear = loci.ticks.UTC[i].year
            idoy = loci.ticks.DOY[i]
            secs = loci.ticks.UTC[i].hour*3600. + loci.ticks.UTC[i].minute*60. + \
                loci.ticks.UTC[i].second

            xout[i,:] = oplib.coord_trans1(sysaxesin, sysaxesout, \
                iyear, idoy, secs, loci.data[i])

        # add  sph to car or v/v convertion if initial sysaxesout was None
        if  aflag == True:
            if returncarsph == 'sph':
                xout = car2sph(xout)
            else: # 'car' needs to be returned
                xout = sph2car(xout)

        return xout

    # -----------------------------------------------
    def car2sph(CARin):
        """
        coordinate transformation from cartesian to spherical

        Parameters
        ==========
            - CARin (list or ndarray) : coordinate points in (n,3) shape with n coordinate points in
                units of [Re, Re, Re] = [x,y,z]

        Returns
        =======
            - results (ndarray) : values after conversion to spherical coordinates in
                radius, latitude, longitude in units of [Re, deg, deg]

        Examples
        ========
        >>> sph2car([1,45,0])
        array([ 0.70710678,  0.        ,  0.70710678])

        See Also
        ========
        sph2car
        """

        if isinstance(CARin[0], numbers.Number):
            CAR = np.array([CARin])
        else:
            CAR = np.asanyarray(CARin)

        res = np.zeros(np.shape(CAR))
        for i in np.arange(len(CAR)):
            x, y, z = CAR[i,0], CAR[i,1], CAR[i,2]
            r = np.sqrt(x*x+y*y+z*z)
            sq = np.sqrt(x*x+y*y)
            if (x == 0) & (y == 0): # on the poles
                longi = 0.
                if z < 0:
                    lati = -90.
                else:
                    lati = 90.0
            else:
                longi = np.arctan2(y,x)*180./np.pi
                lati = 90. - np.arctan2(sq, z)*180./np.pi
            res[i,:] = [r, lati, longi]

        if isinstance(CARin[0], numbers.Number):
            return res[0]
        else:
            return res

    # -----------------------------------------------
    def sph2car(SPHin):
        """
        coordinate transformation from spherical to cartesian

        Parameters
        ==========
            - SPHin (list or ndarray) : coordinate points in (n,3) shape with n coordinate points in
                units of [Re, deg, deg] = [r, latitude, longitude]

        Returns
        =======
            - results (ndarray) : values after conversion to cartesian coordinates x,y,z

        Examples
        ========
        >>> sph2car([1,45,45])
        array([ 0.5       ,  0.5       ,  0.70710678])

        See Also
        ========
        car2sph

        """

        if isinstance(SPHin[0], numbers.Number):
            SPH = np.array([SPHin])
        else:
            SPH = np.asanyarray(SPHin)

        res = np.zeros(np.shape(SPH))
        for i in np.arange(len(SPH)):
            r,lati,longi = SPH[i,0], SPH[i,1], SPH[i,2]
            colat = np.pi/2. - lati*np.pi/180.
            x = r*np.sin(colat)*np.cos(longi*np.pi/180.)
            y = r*np.sin(colat)*np.sin(longi*np.pi/180.)
            z = r*np.cos(colat)
            res[i,:] = [x, y, z]

        if isinstance(SPHin[0], numbers.Number):
            return res[0]
        else:
            return res

    # -----------------------------------------------
    def get_sysaxes(dtype, carsph):
        """
        will return the sysaxes according to the irbem library

        Parameters
        ==========
        - dtype (str) : coordinate system, possible values: GDZ, GEO, GSM, GSE, SM,
                GEI, MAG, SPH, RLL
        - carsph (str) : cartesian or spherical, possible values: 'sph', 'car'

        Returns
        =======
        - sysaxes (int) : value after oner_desp library from 0-8 (or None if not available)

        Examples
        ========
        >>> get_sysaxes('GSM', 'car')
        2

        See Also
        ========
        get_dtype

        """

        #typedict = {'GDZ': {'sph': 0, 'car': 10},
            #'GEO': {'sph': 1, 'car': 11}, 'GSM': {'sph': 22, 'car': 2},
            #'GSE': {'sph': 23, 'car': 3}, 'SM': {'sph': 24, 'car': 4},
            #'GEI': {'sph': 25, 'car': 5}, 'MAG': {'sph': 26, 'car': 6},
            #'SPH': {'sph': 7, 'car': 17}, 'RLL': {'sph': 8, 'car': 18}}

        sysaxes = SYSAXES_TYPES[dtype][carsph]

        return sysaxes

    # -----------------------------------------------
    def get_dtype(sysaxes):
        """
        will return the coordinate system type as string

        Parameters
        ==========
            - sysaxes (int) : number according to the irbem, possible values: 0-8

        Returns
        =======
            - dtype (str) : coordinate system GDZ, GEO, GSM, GSE, SM, GEI, MAG, SPH, RLL
            - carsph (str) : cartesian or spherical 'car', 'sph'

        Examples
        ========
        >>> get_dtype(3)
        ('GSE', 'car')

        See Also
        ========
        get_sysaxes

        """

        for key in SYSAXES_TYPES:
            for subkey in SYSAXES_TYPES[key]:
                if SYSAXES_TYPES[key][subkey] == sysaxes:
                    dtype = key
                    carsph = subkey

        return dtype, carsph

    # -----------------------------------------------
    def get_AEP8(energy, loci, model='min', fluxtype='diff', particles='e'):
        """
        will return the flux from the AE8-AP8 model

        Parameters
        ==========
            - energy (float) : center energy in MeV; if fluxtype=RANGE, then needs to be a list [Emin, Emax]
            - loci (Coords)  : a Coords instance with the location inside the magnetosphere
                 optional      instead of a Coords instance, one can also provide a list with [BBo, L] combination
            - model (str)    : MIN or MAX for solar cycle dependence
            - fluxtype (str) : DIFF, RANGE, INT are possible types
            - particles (str): e or p or electrons or protons

        Returns
        =======
            - float : flux from AE8/AP8 model

        Examples
        ========
        >>> spacepy.irbempy.get_aep8()

        >>> import spacepy.time as spt
        >>> import spacepy.coordinates as spc
        >>> import spacepy.irbempy as ib
        >>> t = spt.Ticktock(['2017-02-02T12:00:00'], 'ISO')
        >>> y = spc.Coords([3,0,0], 'GEO', 'car')
        >>> y.ticks = t
        >>> energy = 1.0 #MeV
        >>> ib.get_AEP8(energy, y, model='max')
        1932209.4427359989

        """
        # find bad values and dimensions

        if particles.lower() == 'e': # then choose electron model
            if model.upper() == 'MIN':
                whichm = 1
            elif model.upper() == 'MAX':
                whichm = 2
            else:
                print('Warning: model='+model+' is not implemented: Choose MIN or MAX')
        elif particles.lower() == 'p': # then choose proton model
            if model.upper() == 'MIN':
                whichm = 3
            elif model.upper() == 'MAX':
                whichm = 4
            else:
                print('Warning: model='+model+' is not implemented: Choose MIN or MAX')
        else:
            print('Warning: particles='+particles+' is not available: choose e or p')

        if fluxtype.upper() == 'DIFF':
            whatf = 1
        elif fluxtype.upper() == 'RANGE':
            whatf = 2
        elif fluxtype.upper() == 'INT':
            whatf = 3
        else:
            print('Warning: fluxtype='+fluxtype+' is not implemented: Choose DIFF, INT or RANGE')

        # need range if whatf=2
        Nene  = 1
        if whatf == 2: assert len(energy) == 2, 'Need energy range with this choice of fluxtype=RANGE'
        ntmax = 1

        #build dummy OMNI dictionary for prep_irbem (AE/AP8 doesn't need these inputs)
        dum_omni = dict()
        magkeys = ['Kp', 'Dst', 'dens', 'velo', 'Pdyn', 'ByIMF', 'BzIMF',\
                        'G1', 'G2', 'G3', 'W1', 'W2', 'W3', 'W4', 'W5', 'W6']
        for key in magkeys:
            dum_omni[key] = [0]*len(loci)

        if isinstance(loci, spc.Coords):
            assert loci.ticks, 'Coords require time information with a Ticktock object'
            d = prep_irbem(ticks=loci.ticks, loci=loci, omnivals=dum_omni)
            E_array = np.zeros((2,d['nalp_max']))
            E_array[:,0] = energy
            # now get the flux
            flux = oplib.fly_in_nasa_aeap1(ntmax, d['sysaxes'], whichm, whatf, Nene, E_array, d['iyearsat'], d['idoysat'], d['utsat'], \
                d['xin1'], d['xin2'], d['xin3'])
        elif isinstance(loci, (list, np.ndarray)):
            BBo, L = loci
            d = prep_irbem(omnivals=dum_omni)
            E_array = np.zeros((2,d['nalp_max']))
            E_array[:,0] = energy
            B_array = np.zeros(d['ntime_max'])
            B_array[0] = BBo
            L_array = np.zeros(d['ntime_max'])
            L_array[0] = L
            # now get the flux
            flux =  oplib.get_ae8_ap8_flux(ntmax, whichm, whatf, Nene, E_array, B_array, L_array)

        else:
            print('Warning: coords need to be either a spacepy.coordinates.Coords instance or a list of [BBo, L]')

        flux[np.where( tb.feq(flux, d['badval'])) ] = np.NaN

        return flux[0,0]

    # -----------------------------------------------
    def _get_Lstar(ticks, loci, alpha, extMag='T01STORM', options=[1,0,0,0,0], omnivals=None):
        """
        This will call make_lstar1 or make_lstar_shell_splitting_1 from the irbem library
        and will lookup omni values for given time if not provided (optional). If pitch angles
        are provided, drift shell splitting will be calculated and "Bmirr" will be returned. If they
        are not provided, then no drift shell splitting is calculated and "Blocal" is returned.

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information
            - loci (Coords class) : containing spatial information
            - alpha (list or ndarray) : pitch angles in degrees; if provided will
                calculate shell splitting; max 25 values
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained below
            - omni values as dictionary (optional) : if not provided, will use lookup table

        Returns
        =======
            - results (dictionary) : containing keys: Lm, Lstar, Bmin, Blocal (or Bmirr),
                Xj (I - the 2nd invariant), MLT
                if pitch angles provided in "alpha" then drift shells are calculated and "Bmirr"
                is returned if not provided, then "Blocal" at spacecraft is returned.

        Examples
        ========
        >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car')
        >>> spacepy.irbempy.Lstar(t,y)
        {'Blocal': array([ 1020.40493286,  3446.08845227]),
            'Bmin': array([ 1019.98404311,  3437.63865243]),
            'Lm': array([ 3.08948304,  2.06022102]),
            'Lstar': array([ 2.97684043,  1.97868577]),
            'MLT': array([ 23.5728333 ,  23.57287944]),
            'Xj': array([ 0.00112884,  0.00286955])}

        Notes
        =====
        External Field
            - 0	   : no external field
            - MEAD	: Mead & Fairfield [1975] (uses 0<=Kp<=9 - Valid for rGEO<=17. Re)
            - T87SHORT: Tsyganenko short [1987] (uses 0<=Kp<=9 - Valid for rGEO<=30. Re)
            - T87LONG : Tsyganenko long [1987] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re)
            - T89	 : Tsyganenko [1989] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re)
            - OPQUIET : Olson & Pfitzer quiet [1977] (default - Valid for rGEO<=15. Re)
            - OPDYN   : Olson & Pfitzer dynamic [1988] (uses 5.<=dens<=50., 300.<=velo<=500.,
                -100.<=Dst<=20. - Valid for rGEO<=60. Re)
            - T96	 : Tsyganenko [1996] (uses -100.<=Dst (nT)<=20., 0.5<=Pdyn (nPa)<10.,
                |ByIMF| (nT)<1=0., |BzIMF| (nT)<=10. - Valid for rGEO<=40. Re)
            - OSTA	: Ostapenko & Maltsev [1997] (uses dst,Pdyn,BzIMF, Kp)
                T01QUIET: Tsyganenko [2002a,b] (uses -50.<Dst (nT)<20., 0.5<Pdyn (nPa)<=5.,
                |ByIMF| (nT)<=5., |BzIMF| (nT)<=5., 0.<=G1<=10., 0.<=G2<=10. - Valid for xGSM>=-15. Re)
            - T01STORM: Tsyganenko, Singer & Kasper [2003] storm  (uses Dst, Pdyn, ByIMF, BzIMF, G2, G3 -
                there is no upper or lower limit for those inputs - Valid for xGSM>=-15. Re)
            - T05	 : Tsyganenko & Sitnov [2005] storm  (uses Dst, Pdyn, ByIMF, BzIMF,
                W1, W2, W3, W4, W5, W6 - no upper or lower limit for inputs - Valid for xGSM>=-15. Re)
            - TS07   : Tsyganenko and Sitnov [2007] model. Uses specially calculated coefficient files.

        OMNI contents
            - Kp: value of Kp as in OMNI2 files but has to be double instead of integer type
            - Dst: Dst index (nT)
            - dens: Solar Wind density (cm-3)
            - velo: Solar Wind velocity (km/s)
            - Pdyn: Solar Wind dynamic pressure (nPa)
            - ByIMF: GSM y component of IMF mag. field (nT)
            - BzIMF: GSM z component of IMF mag. field (nT)
            - G1:  G1=< Vsw*(Bperp/40)2/(1+Bperp/40)*sin3(theta/2) > where the <> mean an average over the
                previous 1 hour, Vsw is the solar wind speed, Bperp is the transverse IMF
                component (GSM) and theta it's clock angle.
            - G2: G2=< a*Vsw*Bs > where the <> mean an average over the previous 1 hour,
                    Vsw is solar wind speed, Bs=|IMF Bz| when IMF Bz < 0 and Bs=0 when IMF Bz > 0, a=0.005.
            - G3:  G3=< Vsw*Dsw*Bs /2000.> where the <> mean an average over the previous 1 hour,
                    Vsw is the solar wind speed, Dsw is the solar wind density, Bs=|IMF Bz| when IMF
                    Bz < 0 and Bs=0 when IMF Bz > 0.
            - W1 - W6: see definition in (JGR-A, v.110(A3), 2005.) (PDF 1.2MB)
            - AL: the auroral index

        Options
            - 1st element: 0 - don't compute L* or phi ;  1 - compute L*; 2- compute phi
            - 2nd element: 0 - initialize IGRF field once per year (year.5);
                n - n is the  frequency (in days) starting on January 1st of each year
                (i.e. if options(2nd element)=15 then IGRF will be updated on the following days of the
                year: 1, 15, 30, 45 ...)
            - 3rd element: resolution to compute L* (0 to 9) where 0 is the recomended value to ensure a
                good ratio precision/computation time
                (i.e. an error of ~2% at L=6). The higher the value the better will be the precision, the
                longer will be the computing time. Generally there is not much improvement for values
                larger than 4. Note that this parameter defines the integration step (theta)
                along the field line such as dtheta=(2pi)/(720*[options(3rd element)+1])
            - 4th element: resolution to compute L* (0 to 9). The higher the value the better will be
                the precision, the longer will be
                the computing time. It is recommended to use 0 (usually sufficient) unless L* is not
                computed on a LEO orbit. For LEO orbit higher values are recommended. Note that this
                parameter defines the integration step (phi) along the drift shell such as
                dphi=(2pi)/(25*[options(4th element)+1])
            - 5th element: allows to select an internal magnetic field model (default is set to IGRF)
                - 0 = IGRF
                - 1 = Eccentric tilted dipole
                - 2 = Jensen&Cain 1960
                - 3 = GSFC 12/66 updated to 1970
                - 4 = User-defined model (Default: Centred dipole + uniform [Dungey open model] )
                - 5 = Centred dipole

        """
        nTAI = len(ticks)
        d = prep_irbem(ticks, loci, alpha, extMag, options, omnivals)
        nalpha = d['nalpha']

        if isinstance(alpha, numbers.Number): # no drift shell splitting
            raise Exception
            lm, lstar, blocal, bmin, xj, mlt = oplib.make_lstar1(nTAI, d['kext'], d['options'], d['sysaxes'],\
                        d['iyearsat'], d['idoysat'], d['utsat'], d['xin1'], d['xin2'], d['xin3'], d['magin'])

        elif nalpha > 0 and nalpha <= d['nalp_max']: # with drift shell splitting
            lm, lstar, bmirr, bmin, xj, mlt = oplib.make_lstar_shell_splitting1(nTAI, nalpha, \
                d['kext'], d['options'], d['sysaxes'], d['iyearsat'], d['idoysat'], d['utsat'], \
                d['xin1'], d['xin2'], d['xin3'], d['degalpha'], d['magin'])

        else:
            print('ERROR: too many pitch angles requested; 25 is maximum')

        # take out all the odd 'bad values' and turn them into NaN
        lm[np.where( tb.feq(lm,d['badval'])) ] = np.NaN
        lstar[np.where( tb.feq(lstar,d['badval'])) ] = np.NaN
        bmin[np.where( tb.feq(bmin,d['badval'])) ] = np.NaN
        xj[np.where( tb.feq(xj,d['badval'])) ] = np.NaN
        mlt[np.where( tb.feq(mlt,d['badval'])) ] = np.NaN

        results = {}
        if nalpha == 0:
            results['Lm'] = lm[0:nTAI]
            results['Lstar'] = lstar[0:nTAI]
            blocal[np.where( tb.feq(blocal,d['badval'])) ] = np.NaN
            results['Blocal'] = blocal[0:nTAI]
            results['Bmin'] = bmin[0:nTAI]
            results['Xj'] = xj[0:nTAI]
            results['MLT'] = mlt[0:nTAI]
        else:
            results['Lm'] = lm[0:nTAI, 0:nalpha]
            results['Lstar'] = lstar[0:nTAI, 0:nalpha]
            bmirr[np.where( tb.feq(bmirr, d['badval'])) ] = np.NaN
            results['Bmirr'] = bmirr[0:nTAI, 0:nalpha]
            results['Bmin'] = bmin[0:nTAI]
            results['Xj'] = xj[0:nTAI, 0:nalpha]
            results['MLT'] = mlt[0:nTAI]

        return results

    # -----------------------------------------------
    def get_Lm(ticks, loci, alpha, extMag='T01STORM', intMag='IGRF', IGRFset=0, omnivals=None):
        """
        Return the MacIlwain L value for a given location, time and model

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information
            - loci (Coords class) : containing spatial information
            - alpha (list or ndarray) : pitch angles in degrees
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - intMag (string) : optional: select the internal field model
                                possible values ['IGRF','EDIP','JC','GSFC','DUN','CDIP']
                                For full details see get_Lstar
            - omni values as dictionary (optional) : if not provided, will use lookup table

        Returns
        =======

            - results (dictionary) : containing keys: Lm, Bmin, Blocal (or Bmirr), Xj, MLT
                if pitch angles provided in "alpha" then drift shells are calculated and "Bmirr"
                is returned if not provided, then "Blocal" at spacecraft is returned. A negative
                value for Lm indicates the field line is closed but particles are lost to the
                atmosphere; the absolute value indicates the L value.

        Examples
        ========

        Notes
        =====

        """
        intMaglookup = {'IGRF': 0, 'EDIP': 1, 'JC': 2, 'GSFC': 3, 'DUN': 4, 'CDIP': 5}
        if intMag not in intMaglookup:
            raise ValueError('Invalid value of intMag: valid values are: {0}'.format(intMaglookup.keys()))
        if IGRFset != 0:
            try:
                assert IGRFset > 0
                ##TODO: test for numeric type
            except AssertionError:
                raise ValueError('IGRFset must be positive-valued and numeric')

        opts = [0, IGRFset, 0, 0, intMaglookup[intMag]]

        results = get_Lstar(ticks, loci, alpha, extMag=extMag, options=opts, omnivals=omnivals)
        dum = results.pop('Lstar')
        return results

    # -----------------------------------------------
    def get_Lstar(ticks, loci, alpha=90, extMag='T01STORM', options=[1,0,0,0,0], omnivals=None):
        """
        This will call make_lstar1 or make_lstar_shell_splitting_1 from the irbem library
        and will lookup omni values for given time if not provided (optional). If pitch angles
        are provided, drift shell splitting will be calculated and "Bmirr" will be returned. If they
        are not provided, then no drift shell splitting is calculated and "Blocal" is returned.

        Parameters
        ==========
            - ticks (Ticktock class) : containing time information
            - loci (Coords class) : containing spatial information
            - alpha (list or ndarray) : optional pitch angles in degrees (default is 90);
                if provided will calculate shell splitting; max 25 values
            - extMag (string) : optional; will choose the external magnetic field model
                                possible values ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89',
                                'OPQUIET', 'OPDYN', 'T96', 'OSTA', 'T01QUIET', 'T01STORM',
                                'T05', 'ALEX', 'TS07']
            - options (optional list or array of integers length=5) : explained below
            - omni values as dictionary (optional) : if not provided, will use lookup table

        Returns
        =======
            - results (dictionary) : containing keys: Lm, Lstar, Bmin, Blocal (or Bmirr), Xj, MLT
                if pitch angles provided in "alpha" then drift shells are calculated and "Bmirr"
                is returned if not provided, then "Blocal" at spacecraft is returned. A negative
                value for Lm indicates the field line is closed but particles are lost to the
                atmosphere; the absolute value indicates the L value. A negative value for Lstar
                indicates the field line is closed but particles are lost to the atmosphere
                before completing a drift orbit; the absolute value indicates the drift shell.

        Examples
        ========
        >>> t = Ticktock(['2002-02-02T12:00:00', '2002-02-02T12:10:00'], 'ISO')
        >>> y = Coords([[3,0,0],[2,0,0]], 'GEO', 'car')
        >>> spacepy.irbempy.Lstar(t,y)
        {'Blocal': array([ 1020.40493286,  3446.08845227]),
            'Bmin': array([ 1019.98404311,  3437.63865243]),
            'Lm': array([ 3.08948304,  2.06022102]),
            'Lstar': array([ 2.97684043,  1.97868577]),
            'MLT': array([ 23.5728333 ,  23.57287944]),
            'Xj': array([ 0.00112884,  0.00286955])}

        Notes
        =====
        External Field
            - 0	   : no external field
            - MEAD	: Mead & Fairfield [1975] (uses 0<=Kp<=9 - Valid for rGEO<=17. Re)
            - T87SHORT: Tsyganenko short [1987] (uses 0<=Kp<=9 - Valid for rGEO<=30. Re)
            - T87LONG : Tsyganenko long [1987] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re)
            - T89	 : Tsyganenko [1989] (uses 0<=Kp<=9 - Valid for rGEO<=70. Re)
            - OPQUIET : Olson & Pfitzer quiet [1977] (default - Valid for rGEO<=15. Re)
            - OPDYN   : Olson & Pfitzer dynamic [1988] (uses 5.<=dens<=50., 300.<=velo<=500.,
                -100.<=Dst<=20. - Valid for rGEO<=60. Re)
            - T96	 : Tsyganenko [1996] (uses -100.<=Dst (nT)<=20., 0.5<=Pdyn (nPa)<10.,
                abs(ByIMF) (nT)<1=0., abs(BzIMF) (nT)<=10. - Valid for rGEO<=40. Re)
            - OSTA	: Ostapenko & Maltsev [1997] (uses dst,Pdyn,BzIMF, Kp)
                T01QUIET: Tsyganenko [2002a,b] (uses -50.<Dst (nT)<20., 0.5<Pdyn (nPa)<=5.,
                abs(ByIMF) (nT)<=5., abs(BzIMF) (nT)<=5., 0.<=G1<=10., 0.<=G2<=10. - Valid for xGSM>=-15. Re)
            - T01STORM: Tsyganenko, Singer & Kasper [2003] storm  (uses Dst, Pdyn, ByIMF, BzIMF, G2, G3 -
                there is no upper or lower limit for those inputs - Valid for xGSM>=-15. Re)
            - T05	 : Tsyganenko & Sitnov [2005] storm  (uses Dst, Pdyn, ByIMF, BzIMF,
                W1, W2, W3, W4, W5, W6 - no upper or lower limit for inputs - Valid for xGSM>=-15. Re)

        OMNI contents
            - Kp: value of Kp as in OMNI2 files but has to be double instead of integer type
            - Dst: Dst index (nT)
            - dens: Solar Wind density (cm-3)
            - velo: Solar Wind velocity (km/s)
            - Pdyn: Solar Wind dynamic pressure (nPa)
            - ByIMF: GSM y component of IMF mag. field (nT)
            - BzIMF: GSM z component of IMF mag. field (nT)
            - G1:  G1=< Vsw*(Bperp/40)2/(1+Bperp/40)*sin3(theta/2) > where the <> mean an average over the
                previous 1 hour, Vsw is the solar wind speed, Bperp is the transverse IMF
                component (GSM) and theta it's clock angle.
            - G2: G2=< a*Vsw*Bs > where the <> mean an average over the previous 1 hour,
                    Vsw is solar wind speed, Bs=|IMF Bz| when IMF Bz < 0 and Bs=0 when IMF Bz > 0, a=0.005.
            - G3:  G3=< Vsw*Dsw*Bs /2000.> where the <> mean an average over the previous 1 hour,
                    Vsw is the solar wind speed, Dsw is the solar wind density, Bs=|IMF Bz| when IMF
                    Bz < 0 and Bs=0 when IMF Bz > 0.
            - W1 - W6: see definition in (JGR-A, v.110(A3), 2005.) (PDF 1.2MB)
            - AL: the auroral index

        Options
            - 1st element: 0 - don't compute L* or phi ;  1 - compute L*; 2- compute phi
            - 2nd element: 0 - initialize IGRF field once per year (year.5);
                n - n is the  frequency (in days) starting on January 1st of each year
                (i.e. if options(2nd element)=15 then IGRF will be updated on the following days of the
                year: 1, 15, 30, 45 ...)
            - 3rd element: resolution to compute L* (0 to 9) where 0 is the recomended value to ensure a
                good ratio precision/computation time
                (i.e. an error of ~2% at L=6). The higher the value the better will be the precision, the
                longer will be the computing time. Generally there is not much improvement for values
                larger than 4. Note that this parameter defines the integration step (theta)
                along the field line such as dtheta=(2pi)/(720*[options(3rd element)+1])
            - 4th element: resolution to compute L* (0 to 9). The higher the value the better will be
                the precision, the longer will be
                the computing time. It is recommended to use 0 (usually sufficient) unless L* is not
                computed on a LEO orbit. For LEO orbit higher values are recommended. Note that this
                parameter defines the integration step (phi) along the drift shell such as
                dphi=(2pi)/(25*[options(4th element)+1])
            - 5th element: allows to select an internal magnetic field model (default is set to IGRF)
                - 0 = IGRF
                - 1 = Eccentric tilted dipole
                - 2 = Jensen&Cain 1960
                - 3 = GSFC 12/66 updated to 1970
                - 4 = User-defined model (Default: Centred dipole + uniform [Dungey open model] )
                - 5 = Centred dipole

        """

        from spacepy import config as config_dict

        def get_ov(fullov, stind, enind):
            '''Chop up omni data for multiprocessing'''
            out = dm.SpaceData()
            keylist = list(fullov.keys())
            dum = keylist.pop(keylist.index('Qbits'))
            for key in keylist:
                out[key] = fullov[key][stind:enind]
            for key in fullov['Qbits']:
                out['Qbits'][key] = fullov['Qbits'][key][stind:enind]
            return out

        def reassemble(result):
            '''Reassemble the results from the multiprocessing'''
            funcs = {'Bmin': np.hstack,
                     'Bmirr': np.vstack,
                     'Lm': np.vstack,
                     'Lstar': np.vstack,
                     'MLT': np.hstack,
                     'Xj': np.vstack}
            out = dm.SpaceData()
            for el in result:
                for key in result[0]:
                    if key in list(out.keys()): #not first chunk
                        out[key] = funcs[key]([out[key], el[key]])
                    else: #first chunk
                        out[key] = el[key].copy()
            return out

        if isinstance(alpha, numbers.Number):
            alpha = [alpha]

        ncpus = config_dict['ncpus']
        ncalc = len(ticks)
        nalpha = len(alpha)

        if ncpus>1:
            import __main__ as main
            if hasattr(main, '__file__'):
                try:
                    from multiprocessing import Pool
                    pool = Pool(ncpus)
                except (ImportError, OSError):
                    ncpus = 1 #if pool setup fails, e.g. Wine, go single
            else:
                ncpus = 1 #won't multiprocess in interactive mode

        if ncpus > 1 and ncalc >= ncpus*2:
            nblocks = ncpus
            blocklen = np.floor_divide(ncalc, ncpus)
            tt, cc = [], []
            if omnivals:
                ov = []
            else:
                ov = None
            for block in range(nblocks):
                startind = block*blocklen
                if block != nblocks-1: #not last block
                    endind = block*blocklen + blocklen
                else:
                    endind = block*blocklen + 2*blocklen #going past the end of an array in a slice is fine
                tt.append(ticks[startind:endind]) #chunk time tags
                cc.append(loci[startind:endind]) #chunk positions
                if omnivals:
                    ov.append(get_ov(omnivals, startind, endind))
            inputs = [[tch, cch, alpha, extMag, options, ov] for tch, cch in zip(tt,cc)]
            result = pool.map(_multi_get_Lstar, inputs)
            DALL = reassemble(result)
        else: # single NCPU, no chunking
            DALL = _get_Lstar(ticks, loci, alpha, extMag, options, omnivals)

        return DALL

    def _multi_get_Lstar(inputs):
        '''
        '''
        ticks = inputs[0]
        loci = inputs[1]
        alpha = inputs[2]
        extMag = inputs[3]
        options = inputs[4]
        omnivals = inputs[5]
        DALL = _get_Lstar(ticks, loci, alpha, extMag, options, omnivals)

        return DALL

    # -----------------------------------------------
    def prep_irbem(ticks=None, loci=None, alpha=[], extMag='T01STORM', options=[1,0,0,0,0], omnivals=None):
        """
        Prepare inputs for direct IRBEM-LIB calls. Not expected to be called by the user.
        """
        # setup dictionary to return input values for irbem
        d= {}
        d['badval'] = -1e31
        d['nalp_max'] = 25
        d['ntime_max'] = 100000
        d['options'] = options
        badval = d['badval']
        nalp_max = d['nalp_max']
        ntime_max = d['ntime_max']

        if ticks is None:
            return d

        UTC = ticks.UTC
        DOY = ticks.DOY
        eDOY = ticks.eDOY
        nTAI = len(ticks)

        # setup mag array and move omni values
        magin = np.zeros((nalp_max,ntime_max),float)
        magkeys = ['Kp', 'Dst', 'dens', 'velo', 'Pdyn', 'ByIMF', 'BzIMF',\
                        'G1', 'G2', 'G3', 'W1', 'W2', 'W3', 'W4', 'W5', 'W6']
        def fakeOMNI(npts, mk):
            fakeomni = {}
            for kk in magkeys:
                fakeomni[kk] = [1]*npts
            return fakeomni

        # get omni values
        if omnivals is None:
            # No OMNI values provided so look up (requires data files)
            if extMag.upper() not in ['0', 'OPQUIET','TS07']:
                import spacepy.omni as omni
                omnivals = omni.get_omni(ticks)
            # UNLESS we're asking for a static model... then we spoof the input as the numbers are irrelevant
            # OR TS07, which uses special files
            elif extMag.upper() == 'TS07':
                omnivals = fakeOMNI(len(ticks), magkeys) #keep this separate, just in case TS07 params ever get passed in the usual way
            else:
                omnivals = fakeOMNI(len(ticks), magkeys)
        if 'G' in omnivals:
            for n in range(1,4):
                dum = omnivals['G'][...,n-1]
                if dum.ndim == 0: dum = np.array([dum])
                omnivals['G{0}'.format(n)] = dum
            del omnivals['G']
        if 'W' in omnivals:
            for n in range(1,7):
                dum = omnivals['W'][...,n-1]
                if dum.ndim == 0: dum = np.array([dum])
                omnivals['W{0}'.format(n)] = dum
            del omnivals['W']

        for iTAI in np.arange(nTAI):
            for ikey, key in enumerate(magkeys):
                magin[ikey, iTAI] = omnivals[key][iTAI]

        # multiply Kp*10 to look like omni database
        # this is what irbem lib is looking for
        magin[0,:] = magin[0,:]*10.

        d['magin'] = magin

        # setup time array
        iyearsat = np.zeros(ntime_max, dtype=int)
        idoysat = np.zeros(ntime_max, dtype=int)
        utsat = np.zeros(ntime_max, dtype=float)
        for i in np.arange(nTAI):
            iyearsat[i] = UTC[i].year
            idoysat[i] = int(DOY[i])
            utsat[i] = (eDOY[i]-np.floor(eDOY[i]))*86400.
        d['iyearsat'] = iyearsat
        d['idoysat'] = idoysat
        d['utsat'] = utsat

        # copy coordinates into array
        # prepare coordinates
        d['sysaxes'] = loci.sysaxes
        xin1 = np.zeros(ntime_max, dtype=float)
        xin2 = np.zeros(ntime_max, dtype=float)
        xin3 = np.zeros(ntime_max, dtype=float)
        if loci.carsph == 'sph':
            xin1[0:nTAI] = loci.radi[:]
            xin2[0:nTAI] = loci.lati[:]
            xin3[0:nTAI] = loci.long[:]
        else:
            xin1[0:nTAI] = loci.x[:]
            xin2[0:nTAI] = loci.y[:]
            xin3[0:nTAI] = loci.z[:]
        d['xin1'] = xin1
        d['xin2'] = xin2
        d['xin3'] = xin3

        # convert external magnetic field flag
        extkeys = ['0', 'MEAD', 'T87SHORT', 'T87LONG', 'T89', 'OPQUIET', 'OPDYN', 'T96', \
                    'OSTA', 'T01QUIET', 'T01STORM', 'T05', 'ALEX', 'TS07']
        assert extMag in  extkeys, 'extMag not available: %s' % extMag
        kext = extkeys.index(extMag.upper())
        d['kext'] = kext

        # calc at given pitch angles 'alpha'?
        degalpha = np.zeros(nalp_max, dtype=float)
        if isinstance(alpha, numbers.Number):
            nalpha = 1
            alpha = [alpha]
        nalpha = len(alpha)
        d['nalpha'] = nalpha
        if nalpha > 0:
            degalpha[0:nalpha] = alpha
        d['degalpha'] = degalpha

        return d